The purpose of this paper is to present the application of interval Linear Parameter Varying
(LPV) identification and fault diagnosis approaches to a real wind turbine. Since wind turbines are
highly non-linear systems when operating in their whole range of operation, a LPV model is used. Real
field data and system identification techniques are used to identify the nominal model as well as its
uncertainty. Fault detection is based on interval LPV observers that are used to generate an adaptive
threshold to enhance the robustness of the fault detection test. Finally, fault isolation is based on an
algorithmthat uses the residual fault sensitivity. Several fault scenarios are used to show the performance
of the proposed approach.